Description
EDIT 6/10/20: If you are making a PR for hacktoberfest, please say so in your PR description so that I can add
the hacktoberfest-accepted label.
This repo needs more algorithms. If you see any missing algorithms, kindly contribute.
Hackotberfest participants are welcome!
I will list some of the algorithms that are up for grabs. However, please check if the algorithm
is already in our repo before you begin working.
Feel free to help me add more items to the list. If you have any questions, ask away!
Some Guidelines:
- Please create 1 pull request per algorithm for ease of review.
- Please do not plagiarise. Implementations must be your own. If you have used help from some article (say Wikipedia), give credit in your script in a comment.
- Give a brief explanation/links of what your script does.
- Give helpful comments where you deem necessary. Don't add comments where it's trivial such as
x = y + z % adds two numbersor is unnecessary. - Use proper variable names and filename. If you are working on prime check, please use a proper file name such as prime_check.m rather than primec.m
- Incase your algorithm required multiple files, create a subdirectory, for example, the kmeans algorithm requires two files, so we have a subdirectory for it. Try not to add unnecessary files.
- This repo is for educational purposes. Please keep that in mind when you are working on a contribution to this repo.
- Following this coding style guideline is recommended for all PRs.
Sorting Algorithms:
- Merge sort
- Insertion Sort
- Radix sort
- Quick sort
- Bubble sort
- Bucket sort
Searching Algorithms:
- Linear Search
- Binary Search
- Quick Search
- Jump Search
Math:
- Factorial
- Fibonacci series
- Prime factors
- Prime check
- Softmax
- Jaccard Similarity
- Greatest Common Divisor
- Euclidean Distance
- Hamming Distance
- Find LCM
- Find HCF
- Sum of arithmetic series
- Sum of geometric series
Machine Learning:
NOTE: Please try to use standard datasets for these problems that are freely available
and perhaps popular, such as the iris dataset. Or datasets that are already inbuilt in Matlab/Octave.
- Linear Regression
- Logistic Regression
- Gradient Descent
- DBScan
- K nearest neighbors
- K medoid clustering
- Fuzzy C-means
- Single Layer Perceptron
- RBF NN